Commercial Real Estate Data Analytics: Where to Get It?

April 18, 2024
6 min

The commercial real estate contains an abundance of data. However, analytics that really benefits professionals is a rare thing to find.

Brokers might spend a significant amount of time and effort collecting data that meets specific criteria. In the end, however, they might realize that all the information they’ve managed to dig, alas, isn’t worth it!

To save time, money, and effort industry specialists rely on commercial real estate data analytics. Its primary role is to provide both buyers and sellers with explicit information about the property market, and property qualities which will help them to make more informed decisions and predictions.

This article is an attempt to provide you with comprehensive information about commercial real estate data science, analytics, and sources to find it.

What’s covered?

  • The sense of commercial real estate data science in terms of the CRE industry
  • The role of data analytics in commercial real estate
  • Types of CRE analytics
  • Top 3 commercial real estate data analytics companies

Let’s get started!

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Commercial Real Estate Data Science


I won’t surprise you with the statement that decisions around commercial real estate are numbers driven. CRE professionals employ data science to make strategic decisions and convince the clients that this certain property would be a good investment.

However, for some people, “data science” may be no more than just a buzzword. Let’s identify what exactly commercial real estate data science means.

Data science is a field that comprises mathematics, statistics, computer science disciplines and incorporates techniques like machine learning, deep learning, cluster analysis, data mining, and visualization.

In terms of the CRE industry, data science is crucial for creating sales strategies, marketing campaigns, etc.



In the near future, data science will have an important role to play, as it will be able to not only improve a business strategy but also improve the way and quality of our lives.

Samira Bouadi, Head of Data Science, BNP Paribas Real Estate

Every year the number of data-driven companies increases because industry professionals experienced the real power of data. Commercial real estate data science allows understanding market trends and different behavior types of their clients.

Since 2017, the proportion of CRE organizations that expect to be “data-driven” has doubled to 56%. Investments in data science capabilities provide CRE professionals with information like area description, the fund available, risk level, expected CAP rate, etc.

The Proportion of Data Driven CRE Organizations

The Proportion of Data Driven CRE Organizations

The results of commercial real estate data science help to shed light on the questions like:

  • Is this the right time to invest in commercial properties?
  • What will my ROI (rent on investment) be in the next two years?
  • How much is my existing portfolio worth?



Data Analytics in Commercial Real Estate


Data analytics provides brokers with up-to-date information from demographic, segmentation, location, or geographic databases, so they can build a commercial real estate strategy based on consumer and market trends and avoid costly mistakes.

A few examples of data analytics in commercial real estate:

  • heatmap analysis
  • projected revenue charts
  • property rental calculators
  • analysis of the tenant’s benefits due to flexible leases
  • customer and traffic information for a retail center
  • staff usage information for office space

Agents and brokers use this information to predict how a specific property will perform in the future and what its possible ROI will be.

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Data provides insights into factors such as rent growth, expense growth, and demographic and migration trends, as well as rent spreads between different asset classes. The future of commercial real estate investment is data and technology, and as this becomes a bigger focal point for the industry, we also will reap benefits, such as increased efficiency and more streamlined processes.

Dori Nolan, Senior Vice President of National Client Services at Berkadia
Type of Commercial Real Estate Analytics
Type of CRE analytics Description
Descriptive Analytics Provides insight into the past, showing what has happened during a given period.

Provides the following CRE metrics:
-Loan-to-Value (LTV)
-Debt Coverage Ratio (DCR)
-Return on Investment (ROI)
Diagnostic Analytics Provides insight into the past, showing why something happened during a given period.

This type sheds light on evidence which may lead to a positive change in your CRE business. Diagnostic analytics is the foundation for predictive and prescriptive analytics.
Predictive Analytics Predictive type is forward-looking analytics.

It helps brokers to forecast their future earnings, highlight the risks, and create an action plan accordingly.

Each type of commercial real estate data analytics can help investors and managers better understand the sources of risk—from asset level to macroeconomic—so they can plan appropriate mitigation measures.

Data suddenly becomes actionable information for facility managers to consistently make the best possible decisions in aligning the portfolio with the overall corporate mission.

Phil Wales, CEO eBusiness Strategies LLC

How to Collect CRE Analytics


There is a vast variety of different CRE data sources (business data, API, customer reviews, videos, social media posts, etc.) that allows data analysts to collect relevant data.


Sources of CRE Analytics

Sources of CRE Analytics

So, how to collect CRE analytics data?

How to Collect CRE Analytics in 5 Steps Ascendix

How to Collect CRE Analytics in 5 Steps


The first step is to collect data from different sources. The second step is to clean and transform the data to make it usable. Then comes exploratory data analysis (third step), which combines visualization and statistics. This step aims to define and refine the selection of variables used in the model.

The fourth step is dedicated to choosing potential models and algorithms that fit the business’s requirements. Data analysts apply machine learning and deep learning techniques and evaluates the results.

The final fifth step is showcasing the results to stakeholders to demonstrate the practical implementation of CRE analytics for their business.



What can CRE analytics do for your organization?

Thanks to CRE data analytics, industry professionals get clear and practical insights for strategic actions that they must adopt by combining data from different sources and advanced analytics technologies.

However, brokers sometimes need a place to store and enter the received data under one hood. In such cases, here comes AscendixRE CRM with advanced functionality and multiple dashboards, each providing a comprehensive look across your real estate and facilities portfolio.

AscendixRE can help you:

  • Enter, store, and track key performance metrics across the commercial real estate portfolio
  • Utilize CRE data analytics results to generate targeted lists of contacts
  • Track required properties, listings, sales, leases, land, capital sources, availabilities
  • Visualize stacking plans, display properties on a map, etc.


Top 3 Commercial Real Estate Data Analytics Companies


#1. Environics Analytics


Environics Analytics


Built over 50 years of best practices in the data and analytics business, the platform enables CRE specialists to gain a deeper understanding of their customers, prospects, and trade areas.

This solution provides access to more than 22,000 variables, including demographics, consumer preferences, area analytics, etc. Using executive reporting dashboards, brokers can share insights with stakeholders.

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#2. Reonomy



The company offers advanced data analytics solutions and a network of data providers gathered in one property intelligence platform. Using Reonomy, CRE agents and brokers can analyze property details, transaction history, occupant data, ownership data.   

Moreover, it includes integrations with 3,100 local county assessors, secretary of state, census data, title companies, commercial data & geospatial providers.  

The received data can be easily integrated into your internal systems. 

#3. Real Capital Analytics


Real Capital Analytics

Real Capital Analytics provides CRE industry players with valuable data from a vast network of independent sources to drive the commercial real estate investment markets.  

The company has recorded over $20 trillion commercial property transactions linked to over 200,000 investor and lender profiles and provided its subscribers with a full micro to the macro view of your chosen market.  

CRE data analytics and research results are published in Capital Trends reports (Global, US, Europe, and Asia), frequently quoted in industry news and academic research. 

Wrapping Up


Data science and analytics in the commercial real estate industry are starting to make waves. Utilizing commercial real estate data analytics within your business presents a great opportunity to have a competitive edge among your peers.

Using various commercial property data in combination with analytics helps you foresee different scenarios and future trends and avoid pitfalls along the way.

CRE data analytics allows to make data-driven decisions faster and reduce risk.

To utilize analytics effectively, you need a solution that offers storing and organizing options for data details. Consider AscedixRE CRM for commercial real estate as a platform where you can handle all the valuable data about your contacts, properties, opportunities, availabilities, and leads.

Read on our case studies and contact us to discover how Ascendix CRM solutions empower companies to improve deal sourcing and client relationships


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Greta James

I am glad that you mentioned that data analytics can provide up-to-date information to build a real estate strategy. I think it is important to make sure that you have all the best and most current information before making major financial commitments. It would be smart to consult a real estate professional that can help with your analytics and research.